The TACO Model: A Strategic Framework for Assessing Operational AI Maturity

You probably know that artificial intelligence (AI) can improve your SaaS business operations.

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However, with the number of AI tools on the market ballooning, it’s extremely difficult to separate hype from substance. Achieving operational excellence means choosing the right tools for the use case. 

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How do you evaluate AI tools for a given use case? As experienced SaaS operators, we recommend using the TACO model promoted by KPMG and other operations experts.

Overview: The TACO Model 

1. Tasker
2. Automator
3. Collaborator
4. Orchestrator

As you move to the right along the AI maturity curve, the potential impact of the application increases. Let’s break down each stage of the TACO model and see what it looks like.

Tasker: Foundational AI Utility

At this initial stage, AI operates as a specialized tool designed for distinct tasks. These systems require explicit instructions from humans and usually lack contextual awareness.  

Example Use Case: Document Summaries

Using a GPT to summarize documents and emails is an example of AI performing a specific, well-defined task on command: extracting key points from lengthy texts. This process does not involve proactive engagement or autonomous decision-making. This task-oriented approach helps streamline information processing, freeing up human resources for more strategic and complex tasks.

Automator: Streamlining Repetitive Workflows

Progressing to this phase, AI begins automating multi-step processes. These systems operate on predefined rules but can’t adapt to novel scenarios. 

Example Use Case: Routine Report Generation

Generating reports on a regular basis is an example of AI executing tasks on a predefined schedule without prompting from a human intervention. AI tools in this phase automatically update PowerPoint presentations, dashboards, and visualizations with fresh data on a daily, weekly, or monthly basis. This eliminates a time-consuming manual process for human operators.

Collaborator: Proactive Partnership

In this stage, AI has the ability to analyze and understand context. This means it can anticipate needs and execute proactively without human prompting. 

Example Use Case: Predictive Chatbots

Predictive chatbots can analyze user behavior and proactively offer suggestions and solutions. These applications make a bigger impact by reducing process times, improving business outcomes, and facilitating operational excellence.

Orchestrator: Autonomous Ecosystem Management

At peak maturity, the AI tool can autonomously coordinate tasks across platforms. This usually involves embedding a layer of AI in all or a majority of decision processes.

Example Use Case: Managing AI/Human Teams

Mature AI tools can autonomously coordinate complex workflows across multiple AI agents and human team members. This means it assigns tasks, facilitates communication, and optimizes performance in real-time. This advanced level of AI application encourages seamless collaboration between humans and AI systems, leveraging the strengths of both to achieve desired business outcomes.

Applying the TACO Framework

Now that you understand the four distinct phases of AI maturity, you can evaluate any AI tool for alignment with its intended use. Follow the steps in this process to think through an AI tool’s capabilities and how they align with each use case. 

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1. Will the AI perform individual tasks with human prompting?
   
   1. Yes: Tasker
   2. No: go to step 2
2. Will the AI execute repetitive multi-step processes with human prompting?
   
   1. Yes: Automator
   2. No: go to step 3
3. Will the AI anticipate outcomes and execute proactively?
   
   1. Yes: Collaborator
   2. No: go to step 4
4. Will the AI coordinate multiple tasks across platforms?
   
   1. Yes: Orchestrator
   2. No: review the process

Example: Anticipating Customer Churn

Here’s what this could look like (this is a hypothetical scenario). 

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Allie runs customer success at HelthYTech, a growing SaaS business with $50M in annual revenue. She wants to use AI to anticipate customer churn and proactively address problems.

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Allie is considering a tool that features predictive analytics. She applies the TACO model, seeing that her intended use case fits in the Collaborator stage. The tool’s predictive capabilities also place it in the Collaborator stage, meaning it aligns with Allie’s intended use case. She implements the tool, which helps her team reduce churn by 23% over six months.

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If you’re looking for more support applying AI to your SaaS business operations, we can help. Contact us today to schedule a consultation.